Effect of Semantic Differences in WordNet-Based Similarity Measures
Assessing the semantic similarity of words is a generic problem in many research fields such as artificial intelligence, biomedicine, linguistics, cognitive science and psychology. The difficulty of this task lies in how to find an effective way to simulate the process of human judgement of word similarity. In this paper, we introduce the idea of semantic differences and commonalities between words to the similarity computation process. Five new semantic similarity metrics are obtained after applying this scheme to traditional WordNet-based measures. In an experimental evaluation of our approach on a standard 28 word pairs dataset, three of the measures outperformed their classical version, while the other two performed as well as their unmodified counterparts.
KeywordsWordNet Measures Semantic Similarity Featured Based Similarity
Unable to display preview. Download preview PDF.
- 1.Budanitsky, A., Hirst, G.: Semantic distance in wordnet: An experimental, application-oriented evaluation of five measures. In: Workshop on WordNet and Other Lexical Resources, 2nd Meeting of the North American Chapter of the Association for Computational Linguistics (2001)Google Scholar
- 2.Fellbaum, C. (ed.): Wordnet: An Electronic Lexical Database, 1st edn. Bradford Books (1998)Google Scholar
- 3.Hai, J., Hanhua, C.: Semrex: Efficient search in a semantic overlay for literature retrieval. Future Generation Computer Systems 11(6), 475–488 (2008)Google Scholar
- 5.Jiang, J.J., Conrath, D.W.: Semantic similarity based on corpus statistics and lexical taxonomy. In: Int. Conf. on Research in Computational Linguistics, pp. 19–33 (1997)Google Scholar
- 6.Leacock, C., Chodorow, M.: Combining local context and wordnet similarity for word sense identification. In: WordNet: A Lexical Reference System and its Application, pp. 265–283 (1998)Google Scholar
- 8.Lin, D.: An information-theoretic definition of similarity. In: 15th Int. Conf. on Machine Learning, pp. 296–304 (1998)Google Scholar
- 13.Resnik, P.: Using information content to evaluate semantic similarity in a taxonomy. In: Int. Joint Conf. on Artificial Intelligence, vol. 14(1), pp. 448–453 (1995)Google Scholar
- 16.Seco, N.: Computational models of similarity in lexical ontologies. Master’s thesis, University College Dublin (2005)Google Scholar
- 18.Wu, Z., Palmer, M.: Verb semantics and lexical selection. In: 32nd Annual Meeting of the Association for Computational Linguistics, pp. 133–138 (1994)Google Scholar
- 19.Ziegler, C.-N., Simon, K., Lausen, G.: Automatic computation of semantic proximity using taxonomic knowledge. In: 15th ACM Int. Conf. on Information and Knowledge Management, pp. 465–474 (2006)Google Scholar